Ultrasonic, infrared, laser and other sensors are being applied in robotics. Although combinations of these have allowed robots to navig- ate, they are only suited for specific scenarios, depending on their limita- tions. Recent advances in computer vision are turning cameras into useful low-cost sensors that can operate in most types of environments. Cam- eras enable robots to detect obstacles, recognize objects, obtain visual odometry, detect and recognize people and gestures, among other possib- ilities. In this paper we present a completely biologically inspired vision system for robot navigation. It comprises stereo vision for obstacle detec- tion, and object recognition for landmark-based navigation. We employ a novel keypoint descriptor which codes responses of cortical complex cells. We also present a biologically inspired saliency component, based on disparity and colour.